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Honeypot trace forensics: The observation viewpoint matters

机译:蜜罐痕迹取证:观察观点很重要

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摘要

In this paper, we propose a method to identify and group together traces left on low interaction honeypots by machines belonging to the same botnet(s) without having any a priori information at our disposal regarding these botnets. In other words, we offer a solution to detect new botnets thanks to very cheap and easily deployable solutions. The approach is validated thanks to several months of data collected with the worldwide distributed Leurre.com system. To distinguish the relevant traces from the other ones, we group them according to either the platforms, i.e. targets hit or the countries of origin of the attackers. We show that the choice of one of these two observation viewpoints dramatically influences the results obtained. Each one reveals unique botnets. We explain why. Last but not the least, we show that these botnets remain active during very long periods of times, up to 700 days, even if the traces they left are only visible from time to time.1
机译:在本文中,我们提出了一种方法,该方法可以识别属于同一僵尸网络的机器在低交互蜜罐中留下的踪迹并将其分组在一起,而无需掌握关于这些僵尸网络的任何先验信息。换句话说,由于价格便宜且易于部署的解决方案,我们提供了一种检测新僵尸网络的解决方案。多亏使用了全球分布式Leurre.com系统收集了数月的数据,该方法得以验证。为了将相关痕迹与其他痕迹区分开来,我们根据平台(即打击目标或攻击者的原籍国)将它们分组。我们表明,这两个观察点之一的选择会极大地影响获得的结果。每个都揭示了独特的僵尸网络。我们解释原因。最后但并非最不重要的一点是,我们证明了这些僵尸网络在很长的时间内(长达700天)仍保持活动状态,即使它们留下的痕迹有时是不可见的。1

著录项

  • 来源
    《Future generation computer systems》 |2011年第5期|p.539-546|共8页
  • 作者

    Van-Hau Pham; Marc Dacier;

  • 作者单位

    School of Computer Science & Engineering, International University, Hochiminh City, Viet Nam;

    Symantec Research Labs, Sophia Antipolis, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    honeypot; attack trace analysis; botnet detection;

    机译:蜜罐;攻击痕迹分析;僵尸网络检测;
  • 入库时间 2022-08-18 02:17:13

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